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Friday, December 28, 2012

The course in question
I recently finished co-teaching Nanothermodynamics - a P-Chem course for nanoscience students covering statistical mechanics, thermodynamics, diffusion, and kinetics. This is the third time I have taught it and the first time I have been really happy with the way my part went. I have also gotten the best teaching evaluations ever, so I know the students were happy with it as well. This blogpost is about why I think it went well and some general musings about teaching in general and teaching thermodynamics in particular.

Repeating questions
I use peer instruction so my "lecture" periods consists mostly of me asking questions that the students answer using Socrative. This year I decided to ask questions about material covered in previous lectures - either the exact same question or a variation of previous questions - and it was a real eye-opener.

Fundamental questions that had received near 100% correct answers one week received at most 50% correct answers one or two weeks later. Clearly the students had done the reading for a particular lecture period but that does not mean they remember it after a few days. Sometimes when I used the exact same question they would remember that the answer was, say, "A" but could not really remember why. So it's not that they are not paying attention.

Less is more
So I decided there was a few key concepts that needed to be reviewed periodically until they "got it" and that was the connection between the equilibrium constant $K$ and the standard free energy change $\Delta G^\circ$ and a molecular understanding of $\Delta H^\circ$ and $\Delta S^\circ$. So I started each lecture period with a few questions such as this one.

Sometime I would spend as much as 50% of the "lecture" period on review. This means something else has to be covered in less detail and this forced me to think much more deeply about what concepts are most important. (It makes it a lot less painful to cut things when you have amble data that 80% won't remember it for more than a few days.) And I think this is why the course was so successful this year: I had, for the first time really, thought very carefully about what to teach and why.

The "textbook" is a problem
Think about the first step in the "design" of a course: pick a textbook. The textbook typically defines what you teach, in what order you teach it, what problems you assign and, as a result, the exam. At best, lectures cover the most difficult parts of the chapters or, at worst, is a mad Powerpoint-fueled dash to cover it all. Often each chapter is given the same number of weeks of coverage regardless of content. I know because I have done all these things myself at some point.

Most textbooks on a particular topic have very similar content. This is not, in my opinion, because textbooks authors have, through exhaustive trial-and-error, converged on an optimum solution but due to a variety of other factors. It is primarily because the audience/customer is not the student but the instructor, because the customer is the one choosing the book, and the customer is a very conservative person for a variety of reasons.

The main reason is that the customer usually has taught the course before and wants, for whatever reason, to change textbooks without making major changes to the course. Furthermore, many instructors do have a "favorite topic" and will not pick the textbook unless that topic is covered in some detail. As a result textbooks rarely leave anything out, no matter how irrelevant the author personally thinks it is.

I would argue that courses end up covering way to many topics, many for no other reason than that they appear in the textbook, and that these topics are in textbooks for no particularly good reason.

A vicious Carnot cycleThe Carnot cycle is in most physical textbooks and is generally a very difficult and abstract concept to do with the maximum efficiency of heat engines. In Molecular Driving Forces, one of the few thermodynamics textbooks that looks quite different from the rest, it is included in Chapter 7 called "The Logic of Thermodynamics" where concepts like heat and work are introduced. The first page of the chapter has pictures of pistons. The opening paragraph states that these new additions to the "toolkit" are "crucial for understanding cyclic energy conversion - in engines, motors, refrigerators, pumps (including your heart), rechargeable batteries, hurricanes, ATP-driven biochemical reactions, oxygen transport around your body, and geophysical cycles of carbon and water, for example." These things are never mentioned again in the rest of the remaining 27 chapters as far as I can tell.

I am not saying these topics are unimportant to chemists, but they are nowhere near as important as say, the relationship between $K$ and $\Delta G^\circ$. However, if you spend more time on the Carnot cycle students will think that it is, and as a result will not really understand either. Example: Who's afraid of Big Bad Thermodynamics?

Tl;dr
For the last few years I have been focussing on how I teach by using simulations and peer instruction. I still think these tools are important; for example, polling the students proved they needed key concepts repeated a few times before they "sink in" and I challenge you to test this yourself with your class - the tool is freely available. But using these tools to teach overly abstract concepts that you or your colleagues never utilize in your jobs only because they appear in the textbook won't get you much further. It's time to take a cold hard look at what you teach and why.

Thermodynamics for the average chemist: some recommendations
* Most chemists think in terms of molecules not equations

* Most chemists would like to understand how to use an equation properly before worrying about where it came from. Consider deemphasizing derivations.

* Most chemists deal with the molecular interpretation of reactions and binding, not phase transitions.

* Most chemists work in solution where volume changes are usually negligible and are usually trying to shift the equilibrium towards products. Consider deemphasizing the concepts of work and efficiency.

* Most $\Delta G^\circ$ measurements are done by measuring $K$. $\Delta S^\circ$ is obtained either by measuring the temperature dependence of $K$ or by measuring $\Delta H^\circ$ calorimetrically and solving for $\Delta S^\circ$ knowing $K$. Consider deemphasizing $\delta S=\delta q_{rev}/T$. Consider introducing $K=e^{-\Delta G^\circ/RT}$ as early as possible.

This is the first time that a fragment based method has been applied to map out a trajectory of an enzyme - on this case the very popular chorismate mutase.

Abstract
We extend the Effective Fragment Molecular Orbital (EFMO) method to the frozen domain approach where only the geometry of an active part is optimized, while the many-body polarization effects are considered for the whole system. The new approach efficiently mapped out the entire reaction path of chorismate mutase in less than four days using 80 cores on 20 nodes, where the whole system containing 2398 atoms is treated in the ab initio fashion without using any force fields. The reaction path is constructed automatically with the only assumption of defining the reaction coordinate a priori. We determine the reaction barrier of chorismate mutase to be 18.3 +/- 3.6$ kcal mol-1 using ONIOM with MP2/cc-pVDZ and EFMO/6-31G(d) for the high and low layers, respectively.

sidenote and totally off topic: you can now reference peoples Google+ profiles directly in blogger in the same way that you do on Google+. Nicely done.

Found this app a while ago, shared it somewhere (probably Twitter) and promised myself I would get back to it. I just spent 30 minutes trying to re-find it and after all this time Twitter is no help. So I am writing this blogpost to remind myself.

There is a free trial and it works great. This will be great for demoing iPad apps or integrating online lecturing with other video.

Sunday, December 23, 2012

Reinventing Discovery
In 2011 I dipped my toe in the open access waters and in 2012 I dived in head first. I come from the GAMESS group, which has always made the source code freely accessible (though under a license) and when it came time to releasing the first standalone software package from my own lab (PROPKA) in 2005 this was done under an open source license. (This year we finally moved all group software to Github.)

So when I came across +Michael Nielsen's Reinventing Discovery in late 2011 I could nod along when I read many of the chapters, but far from all of them. However, the book makes a very compelling case for the idea that secrecy and greed is retarding the progress of science. Shortly after I read the book Elsevier gave a very blatant demonstration of the latter.

The Elsevier Boycott
Sometime in January I became aware of the Research Works Act, which was an outrageous piece of proposed US legislation designed by publishers to squeeze the last few cents out of scientific publishing by making it illegal for papers describing publicly funded research to be made freely accessible online. This lead to a call for boycotting Elsevier, which I signed early on, but it also got me interested in open access publishing (see next section).

I should mention that I have broken the boycott twice already. I agreed to do a review without checking the publisher first and I submitted a paper to an Elsevier journal at the request of a coauthor.

Publishing in the open access journal PLoS ONE
So after some soul-searching on my part we took the plunge an submitted a paper to PLoS ONE. This went alright and 2012 resulted in four PLoS ONE papers and a fifth one submitted. Though PLoS ONE does not count impact as a review criterion I have found the reviews every bit as thorough as for any other journal I have experience with, but you can judge for yourself as I have started posting my reviews on this blog.

arXiv is for research and journals are for CVs plus my own little boycott
Perhaps the most important "open access thing" I did this year is posting preprints on arXiv when we submit to a journal. Just like an open access journal it makes the information freely available, but it does so right away (and discoverable on Google Scholar within a week of deposition) rather than many months later after the review process. If every scientist did this it would be a giant leap for open science and, yes, arXiv does accept manuscripts outside of physics.

Computational Chemistry HighlightsThis year I also initiated the overlay journal Computational Chemistry Highlights. The idea grew from the ensuing on line-discussion of the role publishers and publishing alternatives on Gowers's blog and elsewhere following the Elsevier boycott. I realized, as have many others, that there are two main reasons people publish in conventional journals: dissemination of results and prestige. Dissemination is now a comparatively trivial contribution in the age of the internet and prestige is conferred by the scientific community, not by publishers. CCH is an attempt at generating a platform for conferring prestige on papers that is independent of how its disseminated, using freely available tools like Blogger.com. It will take a while to generate "prestige" for CCH but in the meantime is still provides a useful service to the scientific community by highlighting interesting papers.

Signing reviews
I have started signing my manuscript and proposal reviews. I am not sure what scientific impact this will have but at least it makes science a tiny bit less secretive. On a more practical note I find that I do think a little bit harder about what I write in the review and I am much more careful about doing the review on time.

I can't really emphasize the utility of summarizing your thoughts on a topic via a blogpost enough. If you have clearly thought the issue through it takes no time to write and if not, it helps you to think it through and is well worth the time it takes. I also find it strangely liberating to write knowing that the comment section is there: if I skip something I think is trivial or well known I know the reader can easily ask for clarification.

Thank you for your invitation to review for JCAM. I only review for journals that allow pre-print deposition on servers such as arXiv. According to your instructions to authors this does not appear to be the case, so I must decline. If JCAM does allow for depositions of preprints please let me know.

Saturday, November 24, 2012

A useful equation: $S=R \ln(g)$
Open any P-Chem textbook and you'll find this expression for the entropy (and often a reference to the fact it is inscribed on Boltzmann's tombstone):$$S=k\ln(W)$$ $W$ is the multiplicity of the system, i.e. the number of (microscopic) arrangements producing the same (macroscopic) state, and is given by$$W=\frac{N!}{N_1!N_2!N_3!...N_g!}$$Here $N$ is the number of molecules and $N_i$ is the number of molecules with a particular microscopic arrangement $i$ of which there are $g$ different kinds.

Confused? Believe me you are not the only one, and most scientists never use this form of the equation anyway. Instead they usually assume that all these microscopic arrangements have the same energy or are degenerate (same thing). This means that each macroscopic arrangement is equally likely and $N_1=N_2=...=N/g$. This simplifies the expression for the multiplicity, $$W=g^N$$and entropy$$S=Nk\ln(g)$$significantly and for a mole of molecules we have $$S=R\ln(g)$$This formula relates the entropy to the degeneracy $g$, the number of microscopic arrangements with the same energy

A simple example
Let's say two molecules A and B bind to a receptor R through a single hydrogen bond (indicated by "||||" in the figure) with the same strength.

If you mix equal amounts of A, B, and R you will get more R-A than R-B at equilibrium even though the hydrogen bond strength is the same in the two complexes. This is because molecule A can bind in four different ways while B can only bind one way, i.e. the R-A complex has a degeneracy of four ($g=4$) and the R-B complex has a degeneracy of one ($g=1$). Put another way, the R-A complex is more likely because it has a higher entropy ($S=R\ln(4)$) than the R-B complex ($S=R\ln(1)$).

Ifs, ands, or buts
Of course this is a simplified picture where we only focus on conformational entropy and ignore contributions from translation, rotation and vibration, not only in the complexes but also for free A and B.

Also it is quite unlikely that the hydrogen bond strength for two molecules will be identical or that molecule A will be perfectly symmetrical so that the four binding modes are perfectly degenerate. In general $S=R\ln(g)$ will give you an estimate of the maximum possible value of the conformational entropy.

See for example this interesting blog post on a paper were the authors rationalize the measured difference in binding entropy in terms of conformation. As I point out in the comments section, the conformational entropy difference ($S=R \ln(2)$) is smaller than the measured entropy difference, so there must be other - more important - contributions to the entropy change.

Derivation
If $N_1=N_2=...=N/g$ then $$W=\frac{N!}{(N/g)!^g}$$For large $N$ we can use Stirling's approximation,$x!\approx (x/e)^x$ $$W=\frac{(N/e)^N}{(N/ge)^{(N/g)g}}\\W=\left(\frac{N/e}{(N/e)(1/g)}\right)^N\\W=g^N$$

Thursday, November 15, 2012

Thank you for your invitation to review for FEBS Journal. I only review for journals that allow pre-print deposition on servers such as arXiv. According to your instructions to authors this does not appear to be the case, so I must decline. If FEBS Journal does allow for depositions of preprints please let me know.

Wednesday, November 14, 2012

The program committee found that this was an interesting, relevant and support-worthy application associated with an important and fundamental issue.

Unfortunately, however, when prioritizing support-worthy applications yours was not not given sufficiently high priority to receive support.

Nov 12: European Research Area – Industrial Biotechnology framework (second-round):

We would like to inform you that your proposal EIB.12.031 DZYME was evaluated positively by the ERA-IB Expert Panel in its meeting on the 16th October. Unfortunately, not all positively evaluated proposals can be granted due to a limited budget of some of the national and/or regional funding organisations.

Oct 10: The Danish Council for Independent Research | Technology and Production Sciences (FTP; translated from Danish):

The council finds your application worthy of support. However, the councils funds are insufficient to fund all qualified applications. The council has in this round funded 29 applications out of 280.

Oct 3: The Danish Council for Independent Research | Natural Sciences (FNU; translated from Danish):

Your application was found very worthy of support. This means that your professional qualifications, your CV, and your project was of such quality and character that it would have been funded had there been sufficient funds.

All manuscripts submitted to Physical Chemistry Chemical Physics are initially evaluated by the Editors to ensure they meet the essential criteria for publication in the journal. I’m sorry to say that on this occasion your paper will not be considered further because it is not of sufficient novelty and impact to appeal to our readership.

Sep 29: Journal of Chemical Information and Modeling

"In my judgment, your submission is inappropriate for JCIM; it would be rejected upon full review."

Our previously presented method for high throughput computational screening of mutant activity (Hediger et al., arXiv:1203.2950) is benchmarked against experimentally measured amidase activity for 22 mutants of Candida antarctica lipase B (CalB). Using an appropriate cutoff criterion for the computed barriers, the qualitative activity of 15 out of 22 mutants is correctly predicted. The method identifies four of the six most active mutants with ≥3-fold wild type activity and seven out of the eight least active mutants with ≤0.5-fold wild type activity. The method is further used to screen all sterically possible (386) double-, triple- and quadruple-mutants constructed from the most active single mutants. Based on the benchmark test at least 20 new promising mutants are identified.

Here's the story behind the paper:
I was part of a 3-year EU collaborative project that ended this Spring. One of the sub-projects, headed by Allan Svendsen at Novozymes, was to generate mutants of the lipase CalB that increased its amidase activity, i.e. make it hydrolyze (O=)C-N(H) bonds instead of (O=)C-O bonds. So, every 6-8 months or so Allan would say "we can make a new batch of 5-10 mutants; what should they be?"

Well, for the first two years we didn't really have suggestions since we were developing a method to screen a large number of mutants in a short period of time. So instead ideas for single-mutants were generated using the usual method of educated guessing based, essentially, on visual inspection of the structure. During the last year we were able to computationally test the mutants before they were made to offer real predictions. Towards the end of the project our method was finally sufficiently automated to computationally test all possible double-, triple-, and quadruple mutants that could be made from the single-mutants and we found some very promising ones, but the grant ran out before they could be tested experimentally.

Comparing to experiment we found that had we had the method at the start of the project we would have found most of the mutants with increased amidase activity and ruled out most of the mutants with amidase activity lower than the wild-type.

However, the mutant with highest amidase activity is only 11 times more active than wild-type, and we predict this mutant to have a significantly higher barrer than wild-type. Also, we don't predict right ranking of activity. This makes it difficult to publish in academic journals that focus on impact as we will see next.

Submitting the manuscript
We first sent the paper to Journal of Chemical Information and Modeling who said "In my judgment, your submission is inappropriate for JCIM; it would be rejected upon full review."

Then we considered ChemBioChem but when asked if they consider manuscripts submitted to arXiv they said "ChemBioChem does not consider manuscripts that have been published and available, including on electronic resources such as arXiv. Our statement on this can be found in our Notice to Authors."

Then we tried Physical Chemistry Chemical Physics who said "All manuscripts submitted to Physical Chemistry Chemical Physics are initially evaluated by the Editors to ensure they meet the essential criteria for publication in the journal. I’m sorry to say that on this occasion your paper will not be considered further because it is not of sufficient novelty and impact to appeal to our readership."

So, now the paper is under review at Journal of Molecular Catalysis B: Enzymatic. I had initially gently vetoed that journal since it is published by Elsevier, which I boycott. But when I signed the boycott I was aware that I may have to break that boycott since my name rarely is the only one on the paper. Anyway, in return the paper gets submitted to PLoS ONE (which was my first choice) if this journal rejects.

Should this study be published?
We don't identify a very active mutant. There is little direct correlation between computed barriers and observed activity. The most promising mutants identified computationally are not tested experimentally.

Yes, but this method appears to be the only method capable of computing the effect of mutations on barriers for hundreds of mutants in a practically relevant amount of time. If you are faced with the problem of "which mutants do I start making a month from now" this method is a viable alternative to guessing, which otherwise is the only other option other than random mutagenesis that I can see.

Tuesday, October 30, 2012

Thank you for choosing to publish with PLoS - by now you will have received an email confirmation that your article "A Computational Methodology to Screen Activities of Enzyme Variants" PONE-D-12-07445 has been accepted for publication. Therefore, please find appended an invoice PAB57303 for this article.

Thank you for publishing with PLoS and congratulations on your upcoming publication!

The grant supporting this work has expired while the mss was in review, a protracted process that started in early March, and involved waiting 4 month for the second round of reviews despite numerous inquiries to the editor!

And it's called ... arXiv!arXiv accepts chemistry papers, even though there isn't a "chemistry" category (yet?). If you don't believe me, here are some examples filed under chemical physics (phys.chem-ph):

A few chemistry journals are anti-science and many just appear to be
Few journals appear as welcoming of manuscripts deposited on arXiv as PNAS:

Preprints have a long and notable history in science, and it has been PNAS policy that they do not constitute prior publication.

Most chemistry journal web sites are vague or downright discouraging (I am looking at you, ACS). However, most journal editors I have contacted turn out to be OK with manuscripts being deposited on arXiv.

In fact the only exception so far is ChemBioChem, which flatly refused. I think this is completely anti-science and I intend to boycott these journals like I do for Elsevier journals: no submission, no reviewing, etc.

Did you know that ...arXiv is 5th most cited science journal - well ahead of any chemistry journal?
arXiv papers are "published" on arXiv within roughly 24 hours of deposition?
arXiv articles are discoverable on Google Scholar roughly within a week of deposition on arXiv?

Monday, October 29, 2012

I've been really busy, so haven't kept up with the developments on this paper:

* The reviews arrived on September 24th and can be found below.

* I replied directly to the editor the same day:

Dear xxx
I have just received the reviews. While I believe we can formulate an appropriate response, given the fact that it took 4 months to get the last revision reviewed, we will only re-resubmit if you are willing to make a decision without soliciting further reviews and within a week of receiving the revised manuscript. Otherwise, we will retract the paper as we feel we can get it reviewed considerably quicker at another journal.
Best regards, Jan

The editor replied the same day:

Dear Jan:
I am willing to make a decision within a week of receiving your revised manuscript. I may decide to take such decision assisted by further review(s). This will not affect the time to take my decision.
Best regards
xxx

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, I feel that the manuscript is still not suitable for publication as it currently stands. Therefore, my decision is "Major Revision."

We invite you to submit a revised version of the manuscript that addresses the points of the reviewers. We encourage you to submit your revision within forty-five days of the date of this decision. We apologize for the delay in providing you with the reviews of the manuscript. When your files are ready, please submit your revision by logging on to http://pone.edmgr.com/ and following the Submissions Needing Revision link. Do not submit a revised manuscript as a new submission. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

Please also include a rebuttal letter that responds to each point brought up by the academic editor and reviewer(s). This letter should be uploaded as a Response to Reviewers file.

In addition, please provide a marked-up copy of the changes made from the previous article file as a Manuscript with Tracked Changes file. This can be done using 'track changes' in programs such as MS Word and/or highlighting any changes in the new document.

Yours sincerely,

xxx

Academic Editor

PLOS ONE

Reviewers' comments:

Reviewer #2: The authors have made some minor revisions to the paper to address some of the comments. This method will not be generally reliable for all enzymes: it will fail for mutations that cause significant structural changes, or that cause changes in mechanism (or change which step is rate limiting). It will fail for reactions for which the computational methods are unreliable (these methods are known to have significant failings for a wide variety of reactions, much more than just open shell systems and transition metals; conformation and structural properties are also problematic, e.g. even for simple peptides, and for hydrogen bonds). The proposed method will also fail for reactions in which changes in solvation are significant; it can only be successful where adiabatic mapping profiles can usefully be calculated and provide a useful approximation to the free energy barrier. Clearly also it cannot (and is not designed to) deal with changes in binding affinity (which may be significant, even at high substrate concentrations) or enzyme stability. The discussion should be expanded and clarified to make these points clear, so that the limitations of the proposed procedure are clear to anyone else who may wish to use the method. With those caveats, this type of proposed procedure may be useful to other workers. The reliability of the method for the lipase will only become clear when the authors complete and publish the comparison with experiment, but it will be useful for them to be able to refer to the full technical details of the procedure, so I recommend publication (with these minor revisions) so that their work is not delayed.

Reviewer #3: Hediger et al. propose a method to compute fast enzymatic barriers by optimizing, at a fixed distance length, the conformations obtained by geometric interpolation of reactant and product structure. Due to the large dimension of the system the authors decide to use PM6 semiempirical methods combined with MOZYME, instead of standard SCF.

As discussed by the authors a fast approach to screen the effect of mutations in the barrier will be useful for design. However the authors may show that, in spite of the approximations needed for a fast screening, their method is able to reproduce some experimental data.

A simple control should be the comparison of the obtained barrier with experimental ones. However the obtained value of 6.0 kcal/mol is much lower than the 15-20kcal/mol measured experimentally.

The authors claim that this is because they generate the initial enzyme-substrate (ES) complex based on the product (tetrahedral intermediate, TI) and therefore the active site does not fit optimally the substrate. A simple manner to confirm this is to compare the obtained barrier from the TI to the transition state (TS) with the values obtained for the trypsin (Ishida and Kato, 2003 JACS). Indeed, from the plot of Fig. 7, it seems that the reverse barrier is of aprox. 10 kcal/mol, that it is similar to the one of the trypsin.

It is expected that the reverse barrier is estimated better than the reaction barrier since, in this case, the TS is more similar to the product than to the reactant. However, if the active site of the enzyme is not optimal for the different species along the reaction path it can give serious problem in the barrier and reaction energies calculation, depending on the crystal structure used as an input. It can be explored if a fast optimization (even at classical level) of the binding site itself for the reactant, product and selected TS conformation can improve the barrier estimate.

The authors suggest that the effect of the low barrier is cancelled when computing the relative barrier of mutants against the wild type one, but this has to be proven. I do not find any explanation for the choice for the particular single mutants assessed. It should be better if the authors compare relative barriers obtained for few mutated variants with the experimentally determined kinetics parameters present in literature for that mutants.

Minor details.

A method in which a particular variable (in this case a distance between atoms) is used as a reaction coordinate implies that the user may have prior knowledge of the system. It could be also the case that there is some hidden variable (i.e. a dihedral) and this could lead to estimate wrongly the barrier. This aspect should be mentioned in the method applicability description (i.e. in page 14).

The tetrahedron intermediate acronym should be defined.

In page 2, line 49 there is a typo in 'efficiency'.

In page 3, line 53, in the sentence "the estimation of the reaction barrier of the reaction" one of the 'reaction' has to be deleted.

In page 4, line 31, 'CaLB' should be 'CalB' as in the rest of the manuscript.

In page 8, line 31, 'feasable' should be 'feasible'

===========

PONE-D-12-07445R2

A Computational Methodology to Screen Activities of Enzyme Variants

PLOS ONE

Dear Dr Jensen,

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE.

Your manuscript will now be passed on to our Production staff, who will check your files for correct formatting and completeness. After this review, they may return your manuscript to you so that you can make necessary alterations and upload a final version.

Before uploading, you should check the PDF of your manuscript very closely. THERE IS NO AUTHOR PROOFING. You should therefore consider the corrected files you upload now as equivalent to a production proof. The text you supply at this point will be faithfully represented in your published manuscript exactly as you supply it. This is your last opportunity to correct any errors that are present in your manuscript files.

If you or your institution will be preparing press materials for this manuscript, you must inform our press team in advance. Please contact them at ONEpress@plos.org.

If you have any questions, concerns, or problems, please contact us at plosone@plos.org, and thank you for submitting your work to our journal.

With kind regards,

xxx

Academic Editor

PLOS ONE

Reviewers' comments:

Reviewer #3: The authors have added some sentences to address the comments raised about the applicability of their method to other systems. More importantly, they refer in the text and make available an unpublished study in which they tested their method against experimental activities. From the application paper, the method appears promising to identify potentially interesting mutants, being able to discriminate, with exception of few variants, between 'very active' and 'very inactive' mutants. Therefore I recommend the publication.

One minor typo:

In page 14, line 15: 'reactivity apply: Identifying' should be 'reactivity apply: identifying'

Thursday, October 18, 2012

Project Aim The aim of the project is to develop selective inhibitors for cytochrome P450 (CYP) 17A1 for use in anti-cancer therapy.

Project Strategy Initially, the enzymatic mechanism will be mapped by computational methods. Subsequently and utilizing the knowledge about the mechanism, selective inhibitors will be identified, respectively designed. Finally, potentially interesting ligands will be tested and characterized.

Background and contents When a foreign compound, like a drug, enters the human organism, a number of defence systems are activated. One of them is the ubiquitous multifunctional cytochrome P450 (CYP) family of enzymes that metabolizes about 80 % of drugs, by transforming structurally diverse compounds to water-soluble derivatives by oxidation. The seven most prevalent isoforms of cytochrome P450 enzymes are responsible for almost all metabolism of all known drugs. It has been known for long time that certain CYPs may convert foreign compounds, xenobiotics, to reactive metabolites, and that some of these metabolites may be carcinogenic. New findings – that several endogenous metabolizing CYPs are directly related to various cancer types – have turned the CYPs into direct targets for anti-cancer therapy. In this PhD project, we will focus on the CYP17A1 for three reasons: 1) CYP17A1 is a proven target for treatment of prostate cancer and perhaps also for treatment of breast cancer, 2) the 3D structure of the CYP17A1 complexed with abiraterone and a related compound recently have been determined and published in Nature by Emily Scott, who will be part of the project, and 3) developing selective nonsteroidal inhibitors for CYP17A1 represents a special challenge.CYP17A1 is unique enzyme, because the same enzyme catalyses two subsequent processes: 1) conversion of pregnenolone to 17-a-hydroxypregnenolone (the 17-a-hydroxylase process) and 2) conversion of the 17-a-hydroxypregnenolone to dehydroepiandrosterone (the C17,20-lyase process). Only a limited number of inhibitors of CYP17A1 have been reported in the literature, and nearly all of these are steroidal inhibitors, which also may interact with the androgen receptor. We have in several cases documented that we by computational methods are able to identify new ligands for various drug targets, i.e. b-lactamases, human peptide transporter, the 5-HT2A receptor, and most recently CYP1A2. Based on our experience with modelling enzymatic reactions, especially CYP-mediated reactions and virtual screening, we are confident that it will be possible to identify selective inhibitors for CYP17A1 within the framework of a PhD project.

Perspectives The project is expected to lead to an improved understanding of the structural requirements for ligand binding to and inhibition of CYP 17A1, i.e. to a establish structure/mechanism-activity relationships. The PhD project is also expected to identify/yield selective compounds, which may provide the basis for further work towards therapeutically interesting compounds.

International Collaboration The project is a collaborative project between the Biostructural Research group at University of Copenhagen and associate professor Emily E. Scott at University of Kansas. The project will combine the computational expertise on the CYPs present in the BR group and the experimental expertise present in Scott’s group. The PhD student is expected to spend a considerable time in Scott’s laboratory.

The Applicant An applicant with experience in computational chemistry (in particular molecular dynamics simulations, docking and virtual screening), thermodynamic studies or protein-ligand studies will be preferred. Experimental experience with handling proteins will also be an advantage.

Deadline Deadline for applications is Thursday 8. November 2012 at 12:00.

Sunday, September 23, 2012

This is Figure 10.1 from Dill and Bromberg's Molecular Driving Forces, which is my favorite book on statistical mechanics. It is a beautiful example from a beautiful book.

The chemical potential of a species is defined as the change in free energy with respect to the number of molecules of that species, when temperature, volume, and the number of other species are all kept constant:$$\mu_I=\left(\frac{\partial A}{\partial N_I}\right)_{V,T,N_{J\ne I}}$$Let's explore this for the simple four-bead polymer shown in the figure above. In a previous post I derived the expression for the free energy:$$A=N\varepsilon_0 p_{uf}+TNk\left( p_f\ln(p_f)+p_{uf}\ln\left(\frac{p_{uf}}{4}\right) \right)\\A=\varepsilon_0 N_{uf}+Tk\left( N_f\ln\left(\frac{N_{f}}{N_{f}+N_{uf}}\right)+N_{uf}\ln\left(\frac{N_{uf}}{4(N_{f}+N_{uf})}\right)\right)$$Starting from the latter expression finding the chemical potentials for the folded and unfolded macrostates are: $$\mu_{f}=\left(\frac{\partial A}{\partial N_f}\right)_{V,T,N_{uf}}=kT\ln(p_f)$$ $$\mu_{uf}=\left(\frac{\partial A}{\partial N_{uf}}\right)_{V,T,N_{f}}=\varepsilon_0+kT\ln\left(\frac{p_{uf}}{4}\right)$$The free energy is the sum of the chemical potentials$$A=N_f\mu_f+N_{uf}\mu_{uf}$$Keeping in mind that $N_f=Np_f$ and $N_{uf}=Np_{uf}$ I hope it is obvious to you that this is true.

The chemical potentials are equal at equilibrium
If temperature and volume are constant the change in free energy is given by:$$dA=\mu_fdN_f+\mu_{uf}dN_{uf}$$At equilibrium $dA=0$ and the total number of particles is constant: $dN_f=-dN_{uf}$. Therefore$$\mu_f=\mu_{uf}$$which reduces to the Boltzmann equilibrium distribution:$$kT\ln(p_f)=\varepsilon_0+kT\ln\left(\frac{p_{uf}}{4}\right)\\ \frac{p_{uf}}{p_f}=e^{-( \varepsilon_0-kT\ln(4))/kT}$$The equilibrium constant
The ratio of probabilities is usually referred to as the equilibrium constant $K$:$$K=\frac{p_{uf}}{p_f}$$although it is usually written in terms of concentrations:$$K=\frac{p_{uf}}{p_f}=\frac{N_{uf}}{N_f}=\frac{N_{uf}/V}{N_{f}/V}=\frac{[uf]}{[f]}$$However, this is technically incorrect for two reasons. One reason is that it doesn't work in general. For example:$$\frac{p_ip_j}{p_k}\ne\frac{N_{i}/V N_{j}/V}{N_{k}/V}$$To get around this I write:$$K=\frac{[uf]/[c]^\ominus}{[f]/[c]^\ominus}$$where $[c]^\ominus$ is a standard state concentration, usually defined as 1 molar or 1 molal. Another reason is that when I use concentrations I assume that all polymer molecules are either folded or unfolded, whereas in real solutions some polymers might be stuck together. To correct for this I introduce activity coefficients ($\gamma$) for the folded and unfolded state:$$K=\frac{\gamma_{uf}[uf]/[c]^\ominus}{\gamma_f[f]/[c]^\ominus}=\frac{a_{uf}}{a_f}$$In other words for real (i.e. non-ideal) solutions, the equilibrium constant must be written in terms of activities $(a)$ instead of concentrations

The standard chemical potential and the standard state
The general expression for the chemical potential of a macrostate is:$$\mu_{i}=\varepsilon_i +kT\ln\left(\frac{p_{i}}{g_i}\right)$$which can be rewritten as $$\mu_{i}=\mu_{i}^\ominus+ kT\ln(p_{i})\text{ where }\mu_{i}^\ominus=\varepsilon_i-kT\ln(g_i)$$ $\mu_{i}^\ominus$ is called the standard statechemical potential and is the chemical potential for $p_i=1$, i.e. for pure macrostate $i$, whereas $\mu_{i}$ is the chemical potential for macrostate $i$ in equilibrium with macrostate $j$. Since the chemical potentials are equal at equilibrium, $\mu_i=\mu_j$ can be rearranged to give an expression for the equilibrium constant in terms of the standard state chemical potentials$$K=\frac{p_i}{p_j}=e^{-(\mu_i^\ominus-\mu_j^\ominus)/kT}$$However, in order to express $K$ in terms of something that resembles concentrations, namely activities,$$a_i=\gamma_i\frac{[i]}{[c]^\ominus},$$we define the chemical potential in terms of activities as well:$$\mu_{i}=\mu_{i}^\ominus+ kT\ln(a_{i})$$The standard state chemical potential is the chemical potential for a 1 M ideal solution of particles that don't bind each other: $a_i=1$, i.e. $[i]=[c]^\ominus$ and $\gamma_i=1$.